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Rounding behaviour of professional macro-forecasters

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  • Clements, Michael P.

Abstract

The rounding of point forecasts of CPI inflation and the unemployment rate by U.S. Professional Forecasters is modest. There is little evidence that forecasts are rounded to a greater extent in response to higher perceived uncertainty surrounding future outcomes. There is clear evidence that the probability of decline forecasts are rounded: over half of the forecast probabilities of decline in the current quarter are multiples of ten. It is found here that the rounding of these probabilities correlates with worse accuracy, although it is also of note here that worse (less accurate) forecasters might round more as opposed to the degree of rounding per se worsening accuracy. By simulating the loss from rounding for a set of efficient forecasters, it is demonstrated that the explanation that respondents round otherwise efficient forecasts is implausible, and that the contribution of rounding is of minor importance.

Suggested Citation

  • Clements, Michael P., 2021. "Rounding behaviour of professional macro-forecasters," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1614-1631.
  • Handle: RePEc:eee:intfor:v:37:y:2021:i:4:p:1614-1631
    DOI: 10.1016/j.ijforecast.2021.03.003
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    Cited by:

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    2. Cornand, Camille & Hubert, Paul, 2022. "Information frictions across various types of inflation expectations," European Economic Review, Elsevier, vol. 146(C).
    3. Camille Cornand & Paul Hubert, 2021. "Information frictions in inflation expectations among five types of economic agents," Working Papers 2116, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    4. Camille Cornand & Paul Hubert, 2021. "Information frictions in inflation expectations among five types of economic agents," Working Papers hal-03468918, HAL.
    5. Zhao, Yongchen, 2023. "Internal consistency of household inflation expectations: Point forecasts vs. density forecasts," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1713-1735.

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